Portrait of Yajie Bao

Yajie Bao

Statistics · Machine Learning

Publications

Research

# Equal contribution · * Corresponding author

2026

  1. Shape-Adaptive Conditional Calibration for Conformal Prediction via Minimax Optimization

    Yajie Bao#, Chuchen Zhang#, Zhaojun Wang, Haojie Ren, and Changliang Zou

    arXiv preprint

  2. Conformal Robustness Control: A New Strategy for Robust Decision

    Yang Hu, Jieren Tan, Changliang Zou, Yajie Bao*, and Haojie Ren*

    ICLR · Oral

2025

  1. Optimal Model Selection for Conformalized Robust Optimization

    Yajie Bao, Yang Hu, Haojie Ren, Peng Zhao, and Changliang Zou

    arXiv preprint

  2. CAP: A General Algorithm for Online Selective Conformal Prediction with FCR Control

    Yajie Bao, Yuyang Huo, Haojie Ren, and Changliang Zou

    Journal of Machine Learning Research

  3. Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach

    Qian Peng, Yajie Bao*, Haojie Ren*, Zhaojun Wang, and Changliang Zou

    ICML

  4. Error-quantified Conformal Inference for Time Series

    Junxi Wu, Dongjian Hu, Yajie Bao*, Shu-Tao Xia*, and Changliang Zou

    ICLR

2024

  1. Selective Conformal Inference with False Coverage-statement Rate Control

    Yajie Bao, Yuyang Huo, Haojie Ren, and Changliang Zou

    Biometrika

  2. Provable Benefits of Local Steps in Heterogeneous Federated Learning for Neural Networks: A Feature Learning Perspective

    Yajie Bao, Michael Crawshaw, and Mingrui Liu

    ICML

2023

  1. Semi-Profiled Distributed Estimation for High-Dimensional Partially Linear Model

    Yajie Bao and Haojie Ren

    Computational Statistics & Data Analysis

  2. Global Convergence Analysis of Local SGD for Two-layer Neural Network without Overparameterization

    Yajie Bao, Amarda Shehu, and Mingrui Liu

    NeurIPS

  3. Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds

    Michael Crawshaw, Yajie Bao, and Mingrui Liu

    NeurIPS

  4. EPISODE: Episodic Gradient Clipping with Periodic Resampled Corrections for Federated Learning with Heterogeneous Data

    Michael Crawshaw, Yajie Bao, and Mingrui Liu

    ICLR

2022

  1. Varying Coefficient Linear Discriminant Analysis for Dynamic Data

    Yajie Bao and Yuyang Liu

    Electronic Journal of Statistics

  2. Fast Composite Optimization and Statistical Recovery in Federated Learning

    Yajie Bao, Michael Crawshaw, Shan Luo, and Mingrui Liu

    ICML

  3. Byzantine-Tolerant Distributed Multiclass Sparse Linear Discriminant Analysis

    Yajie Bao, Weidong Liu, Xiaojun Mao, and Weijia Xiong

    UAI

2021

  1. One-Round Communication Efficient Distributed M-Estimation

    Yajie Bao and Weijia Xiong

    AISTATS